Population Density Research Articles

Dengue hemorrhagic fever prediction in coastal area using geographically weighted regression

Dengue hemorrhagic fever (DHF) is still a health problem globally, including in Indonesia. Geographical and climatic conditions in coastal areas are different from other areas, which may impact differences in environmental risk factors for dengue. This study aims to create a prediction model for the incidence of DHF in coastal areas. The research was conducted in Bantul Regency, Indonesia, involving data from 2015-2019. Dengue incidence data were collected from the health office. Climatic data were from climatology station. Data on altitude and shoreline distance were obtained by geographic information system (GIS) processing. Population density and wide settlement area are obtained from the Bureau of Statistics. The geographically weighted regression (GWR) analysis was carried out using GWR4. The results showed that GWR with a weighting of Fixed Bi-Square Kernel obtained an R2 value of 0.7768, better than the global model (R2 0.5254). It indicates that DHF (Y) in Bantul Regency is 77.68% determined by population density (X1), altitude (X2), settlement area (X3), shoreline distance (X4) and rainfall (X5) and the remaining 22.32% are influenced by other variables which are not investigated. Geographically, the predictor variables explain the DHF incidence with a strong category in the central region, and weak in coastal area.

Dynamical behaviors of autonomous and nonautonomous models of generalist predator–prey system with fear, mutual interference and nonlinear harvesting

In this study, we explore a predator–prey model to evaluate the impacts of fear, mutual interference, and harvesting, as these factors play crucial roles in modifying population dynamics, trophic cascades, and species interactions. Additionally, we enhance the model to incorporate the seasonality of specific ecological factors across time. The autonomous and associated nonautonomous models have undergone thorough mathematical analysis and extensive numerical simulations in the course of the study. We conduct a fundamental differential sensitivity analysis to discern the key parameters influencing both prey and predator populations within the ecosystem. Through numerical investigations of the autonomous model, we notice that in the presence (absence) of harvesting, the mutual interference among predators destabilizes (stabilizes) the coexisting equilibrium. The fear effect significantly reduces the densities of prey and predator populations, and destabilizes the coexisting equilibrium by producing multiple stability switches. The survival of predators substantially depends on the focal prey if their growth from other food sources is relatively low. Notably, the harvesting of predators is beneficial and promotes the coexistence of species only when their growth from other food sources is too much. Moreover, the system shows bistability, tristability, and multiple limit cycles under identical ecological conditions. We also show various phenomena that manifest within the seasonally forced model, including the emergence of periodic solutions, higher periodic solutions, bursting patterns, and chaotic dynamics. Remarkably, the influence of seasonal forcing possesses the capability to govern the chaotic dynamics by giving rise to an exceedingly quasi-periodic arrangement in the prey and predator densities.

Crowd Analyzer using Trilateration and Keep Alive Signals

Tracking mobile phones in a specific area is crucial for assessing population density and understanding crowd dynamics. Traditional methods rely on Wi-Fi and GPS, but offline techniques like cell tower triangulation offer valuable insights even in areas with limited connectivity. By analyzing the number of mobile phones present, estimated through trilateration using signals from the phone's keep-alive signal, one can accurately estimate the crowd size. This information aids in urban planning, transportation management, event organization, and business strategies. Empowered with such data, decision-makers can optimize resource allocation, enhance safety measures, and improve overall societal well-being through informed decision-making.

Socio-Economic and Demographic Factors Affecting Adoption of Electric Vehicles in India

The purpose of this study is to analyze the diverse socio-economic and demographic determinants that impact the adoption and growth of electric vehicles (EVs) in India. Quantitative research was conducted utilizing data from the Prowess IQ database. Growth of Electric Vehicles (GEV) is represented through the proxy of total income of ten prominent Indian EV manufacturing companies for eight years from 2016 to 2023. This is analyzed against nine independent variables including GDP, Per Capita Income, Age of Company, Population Density, Average Petrol/Diesel Price, Price of Electricity Per Unit, Average Household Electricity Consumption, and Vehicle Electricity Consumption, data for which was extracted from governmental and company websites. The study employed statistical methods, such as correlation and regression analysis, to examine the associations between the dependent and independent variables. The results depict notable positive correlations with GDP, per capita income, age of company, and population density, and negative correlations with the price of electricity and diesel. Regression analysis further substantiated six variables (population density, petrol prices, per capita income, GDP, diesel prices, and average household electricity consumption) as statistically significant contributors to GEV in India These findings point towards the need to leverage the positive drivers and mitigate the effects of negative correlates. Policies offering financial support tailored to demographic and economic contexts, might help achieve accelerated and sustainable growth for EVs in India. This study highlights the unique impact of demographic elements like population density on the EV market in India.

Rapid evolution of consumptive and non-consumptive predator effects on prey population densities, bioenergetics and stoichiometry.

Predators can strongly influence prey populations not only through consumptive effects (CE) but also through non-consumptive effects (NCE) imposed by predation risk. Yet, the impact of NCE on bioenergetic and stoichiometric body contents of prey, traits that are shaping life histories, population and food web dynamics, is largely unknown. Moreover, the degree to which NCE can evolve and can drive evolution in prey populations is rarely studied. A 6-week outdoor mesocosm experiment with Caged-Fish (NCE) and Free-Ranging-Fish (CE and NCE) treatments was conducted to quantify and compare the effects of CE and NCE on population densities, bioenergetic and stoichiometric body contents of Daphnia magna, a keystone species in freshwater ecosystems. We tested for evolution of CE and NCE by using experimental populations consisting of D. magna clones from two periods of a resurrected natural pond population: a pre-fish period without fish and a high-fish period with high predation pressure. Both Caged-Fish and Free-Ranging-Fish treatments decreased the body size and population densities, especially in Daphnia from the high-fish period. Only the Free-Ranging-Fish treatment affected bioenergetic variables, while both the Caged-Fish and Free-Ranging-Fish treatments shaped body stoichiometry. The effects of CE and NCE were different between both periods indicating their rapid evolution in the natural resurrected population. Both the Caged-Fish and Free-Ranging-Fish treatments changed the clonal frequencies of the experimental Daphnia populations of the pre-fish as well as the high-fish period, indicating that not only CE but also NCE induced clonal sorting, hence rapid evolution during the mesocosm experiment in both periods. Our results demonstrate that CE as well as NCE have the potential to change not only the body size and population density but also the bioenergetic and stoichiometric characteristics of prey populations. Moreover, we show that these responses not only evolved in the studied resurrected population, but that CE and NCE also caused differential rapid evolution in a time frame of 6 weeks (ca. four to six generations). As NCE can evolve as well as can drive evolution, they may play an important role in shaping eco-evolutionary dynamics in predator-prey interactions.

Identifying determinants of spatial agglomeration of healthcare resources by using spatial econometric methods: a longitudinal study in China

BackgroundHealthcare resources are necessary for individuals to maintain their health. The Chinese government has implemented policies to optimize the allocation of healthcare resources and achieve the goal of equality in healthcare for the Chinese people since the implementation of the new medical reform in 2009. Given that no study has investigated regional differences from the perspective of healthcare resource agglomeration, this study aimed to investigate China’s healthcare agglomeration from 2009 to 2017 in China and identify its determinants to provide theoretical evidence for the government to develop and implement scientific and rational healthcare policies.MethodsThe study was conducted using 2009–2017 data to analyze health-resource agglomeration on institutions, beds, and workforce in China. An agglomeration index was applied to evaluate the degree of regional differences in healthcare resource allocation, and spatial econometric models were constructed to identify determinants of the spatial agglomeration of healthcare resources.ResultsFrom 2009 to 2017, all the agglomeration indexes of healthcare exhibited a downward trend except for the number of institutions in China. Population density (PD), government health expenditures (GHE), urban resident’s disposable income (URDI), geographical location (GL), and urbanization level (UL) all had positive significant effects on the agglomeration of beds, whereas both per capita health expenditures (PCHE), number of college students (NCS), and maternal mortality rate (MMR) had significant negative effects on the agglomeration of institutions, beds, and the workforce. In addition, population density (PD) and per capita gross domestic product (PCGDP) in one province had negative spatial spillover effects on the agglomeration of beds and the workforce in neighboring provinces. However, MMR had a positive spatial spillover effect on the agglomeration of beds and the workforce in those regions.ConclusionThe agglomeration of healthcare resources was observed to remain at an ideal level in China from 2009 to 2017. According to the significant determinants, some corresponding targeted measures for the Chinese government and other developing countries should be fully developed to balance regional disparities in the agglomeration of healthcare resources across administrative regions.

Phytoplankton species and traits response to a gradient of urbanization in subtropical lowland streams

AbstractLotic environments are among the most vulnerable aquatic ecosystems, and changes occurring in them happen faster than our capacity to measure the impacts, with the choice of community attributes that best reflect these disturbances still unclear. In this study, we evaluated the response of phytoplankton species and species traits along a gradient of urbanization in lowland streams. To do this, we sampled nine streams in three areas classified as densely populated (DP), low populated (LP), and rural areas (RA) during the four seasons (n = 108), considering relevant limnological variables (including metals, herbicides, and inorganic nutrients) and phytoplankton. Phytoplankton was analysed using taxonomic and morpho‐functional traits approaches. We used several multivariate analyses to assess phytoplankton species and trait distribution among stream groups (DP, LP, RA) and identify their environmental drivers. We found that phytoplankton responded to the urbanization gradient at both taxonomic and functional levels. However, this response was mediated by the land use (urban vs. rural) rather than its intensity. The main stressors detected were eutrophic conditions and organic matter contamination, which differed among groups (DP‐LP and RA). Both approximations indicated eutrophic, organically enriched conditions, but the situation varied among seasons and stream groups. The response of the taxonomic approach was clearer than the traits‐based approach, showing differences in density only between stream groups in the summer and the spring. Phytoplankton was responding to the gradient of urbanization in these subtropical lowland streams, but the seasonality, especially temperature and changes in the water column mixing also mediate the effect.

Antibiotics Sensitivity Reaction of salmonella Species Isolated from Ready-to-Eat Porridge Beans Sold in Federal Polytechnic of Oil and Gas Bonny of Rivers State

Salmonella specie is one of the four key global causes of diarrhoeal diseases. In this research we investigated the frequency occurrence of salmonella species isolated from ready-to-eat porridge beans sold from vendors in the proximity of federal polytechnic of oil and gas bonny island. A total of 40 samples were purchased from four different food vendors in four different spots [vendor 1(The first spot), vendor 11(second spot), vendor 111(third spot) and vendor 1V (fourth spot)] between February and May 2024.All samples were processed and analysed using standard culturebased, biochemical methods and antibiotic susceptibility test assays to confirm salmonella isolates. The highest total occurrence of heterotrophic bacteria population densities were: vendor1 4.0.0×105CFU/g; vendor11 4.4×107CFU/g, vendor111 4.5×102CFU/g and vendor 1V 4.2×109CFU/g. The highest total occurrence of salmonella population density were, for vendor1 3.9×102, Vendor11 2.7×104 , Vendor111 4.1×105,Vendor1V 4.4×103 respectively. Antibiotics susceptibility test was performed for the isolates which exhibited that all of them were susceptible to Ciprofloxacin (CPR)-5 g, Nitrofurantoin (NIT)-30 g, Oflotaxin (OFL)-5 g, were susceptible to Salmonella species. While Gentamicin (GEN)-10 g, and Cefuroxime (CXM)-5 g, were intermediate and Finally, Augmentin (AUG)-30 g, Cefuroxime (CAZ)-30 g, and Cefuroxime (CRX)-30 g were resistant to Salmonella species. Therefore, it can be stated that ready-to-eat porridge beans sold in the proximity of FPOG environment are possible route of transmission for Salmonella species. However, due to lack of intense antibiotic resistance among these bacteria, most of them can be treated with the antibiotics available in the market. Nonetheless, strict monitoring and regular surveillance is necessary.

Spatial-temporal evolution and prediction of carbon storage in Mohe city by linking the logistic-CA-Markov and InVEST models

Carbon storage plays a vital role in the provision of ecosystem services, and the alteration of land use has a profound influence on the carbon storage capacity of ecosystems. Therefore, in this study, two scenarios of natural evolution scenario (NES) and ecological conservation scenario (ECS) were set up based on the development of Mohe City,China. Meanwhile, a coupled model of LUCC and ecosystem carbon storage was established using Logistic-CA-Markov and InVEST models, as well as optimal parameters_based geographical Detector and GeoDa, to predict the distribution and change of ecosystem carbon storage based on LUCC in the future. The effects of different influencing factors on the spatial differentiation of carbon storage were also explored. The results show that: (1) From 1980 to 2020, the land use type in Mohe City was dominated by the forest and its area decreased; the area of wetland increased. From 2020 to 2040, ecological benefits will be shown under the ECS, with an increase in forest and a slower expansion of built-up. (2) Carbon loss in Mohe City from 1980 to 2020 was 4.04Tg. Under the ECS carbon storage increased slightly by 0.2Tg. Soil carbon storage was the main carbon pool in Mohe City, and forest was the largest contributor. The carbon storage of Mohe city in 2030 and 2040 has a strong positive spatial correlation. Hot spots in more than a cold spots area, the high value area is concentrated in the east, low concentrated in urban areas. (3) Apart from LUCC, mean annual precipitation was the most significant factors affecting the spatial differentiation variability of carbon storage. The interactions of mean annual precipitation and population density with other factors exhibit a non-linear enhancement,which had a coefficient of 21.91%. This study contributes to a deeper understanding of the relationship between LUCC and carbon storage.

Exposure of Urban European Hedgehogs (Erinaceus europaeus) to Toxoplasma gondii in Highly Populated Areas of Northeast Spain

Toxoplasma gondii is a generalist zoonotic parasite that involves a wide range of warm-blooded animals as intermediate hosts and felines as definitive hosts. Recent studies have proved significant positive associations between human population density and T. gondii seroprevalence in wildlife. However, there is limited data regarding T. gondii wildlife in urban areas, where the highest human density occurs. The present study aimed to analyse the T. gondii exposure in urban hedgehogs from the Metropolitan Area of Barcelona, NE Spain. One hundred eighteen hedgehogs were analysed for the presence of antibodies (modified agglutination test; n = 55) and parasite DNA (qPCR; heart = 34; brain = 60). Antibodies were detected in 69.09% of hedgehogs. T. gondii DNA was not detected in any of the analysed samples. The present study reports a high T. gondii seroprevalence in urban hedgehogs in areas surrounding Barcelona, the most densely human-populated area of NE Spain, reinforcing the association between human population density and environmental T. gondii oocysts. The lack of detection by molecular techniques warrants more studies. In the last few decades, the distribution and abundance of European hedgehogs have declined, including their urban populations. Further research is needed to investigate the impact of T. gondii on hedgehog populations.

Exploring Drivers of Wildfires in Spain

Wildfires play a dual role in ecosystems by providing ecological benefits while posing catastrophic events; they also inflict non-catastrophic damage and yield long-term effects on biodiversity, soil quality, and air quality, among other factors, including public health. This study analysed the key determinants of wildland fires in Spain using openly available spatial data from 2008 to 2021, including fire perimeters, bioclimatic variables, topography, and socioeconomic datasets, at a resolution of 1 km2. Our methodology combined principal component analysis (PCA), linear regression analysis, and one-way analysis of variance (ANOVA). Our findings show that scrub/herbaceous vegetation (average 63 ± 1.45% SE) and forests (average 19 ± 0.76% SE) have been highly susceptible to wildfires. The population density exhibited a robust positive correlation with wildfire frequency (R2 = 0.88, p < 0.0001). Although the study provides insights into some fire-related climatic drivers over Spain, it includes only temperature and precipitation-based variables and does not explicitly consider fuel dynamics. Therefore, a more advanced methodology should be applied in the future to understand the local specifics of regional wildfire dynamics. Our study identified that scrub/herbaceous areas and forests near densely populated regions should be prioritised for wildfire management in Spain, particularly under changing climate conditions.

Agricultural drought-driven mechanism of coupled climate and human activities in the karst basin of southern China.

Timely and accurate agricultural drought monitoring and drought-driven mechanism analysis in karst basins in the context of global warming are highly important for drought disaster monitoring and sustainable ecological development in a basin. In this study, based on MODIS data, meteorological and topographic data and land use data from 2001 to 2020, we used the Sen slope, the Mann-Kendall test and a geographic detector to explore the driving mechanisms of agricultural drought caused by climate change and human activities in the karst basin of southern China from 2001 to 2020. The results showed that (1) the spatial distribution of the TVDI in the karst basin in southern China has obvious regional characteristics, showing a decreasing trend from west to east. (2) According to the interannual trend of drought, the degree of drought in the South China karst basin exhibited a weakening trend over the last 20 years, with the most severe drought occurring in 2003. Regarding the seasonal change in the TVDI, drought in spring, summer and autumn exhibited a decreasing trend, while that in winter exhibited an increasing trend, and the drought intensity decreased in the following order: spring (0.58) > autumn (0.53) > summer (0.5) > winter (0.48). (3) Single-factor detection the results showed that rainfall, temperature and elevation were the main factors driving aridification in the study area; multifactor coupling (mean) drove drought in descending order: rainfall (q = 0.424) > temperature (q = 0.340) > elevation (q = 0.219) > land use (q = 0.188) > population density (q = 0.061) > slope (q = 0.057). Therefore, revealing the mechanism of agricultural drought in karst basins through the study of this paper has important theoretical significance and provides technical guidance for drought relief in karst areas.

Assessing the relationship between urbanization and plastic litter on sandy beaches in California, USA

Urbanization can increase the threat plastic litter poses to beaches around the world. However, many oceanic beaches lack baseline data on how urbanization may be altering plastic litter abundance. Here, I documented the abundance and type of plastic litter at 23 oceanic beaches that spanned an urbanization gradient (as measured by population density) along the California, USA coast in October 2023. Across all 23 sites, I found that urbanization significantly increased abundance for all types of plastic litter including (large microplastic litter 2–5 mm; mesoplastic 5–25 mm; macroplastic >25 mm). I also found that urban beaches had significantly more plastic litter (132.7 pieces/m2 ± 84.2 S.D.) than non-urban beaches (67.4 pieces/m2 ± 30.9 S.D.). In addition, I found that urban beaches had significantly higher abundances of cigarette butts, hard plastic, and foamed plastic than non-urban beaches. Collectively, my findings suggest that plastic litter pollution poses an important threat to California beaches, that oceanic beaches in more urban areas may be more impacted by this threat over time, and that plastic waste from recreation (both on and off-shore) could be an important source of pollution.

Data on four species of Longidorus Micoletzky, 1922 (Nematoda: Longidoridae) from southern and southeastern Iran, including description of a new species.

Four species of the genus Longidorus were recovered from southern (Bushehr province) and southeastern (Southern Khorasan province) Iran. The first species, L. paratabrizicus n. sp. represents a new member to the genus and is characterised by 4.8-5.6 mm long females with anteriorly flattened lip region separated from the rest of the body by depression, amphidial fovea pocket-shaped without lobes, tail conical, dorsally convex, ventrally almost straight with bluntly rounded tip and males in population. By having similar lip region and tail shape, the new species most closely resembles five species viz. L. artemisiae, L. globulicauda, L. patuxentensis, L. sturhani, and L. tabrizicus. It represents the cryptic form of the last species. The second species belongs to L. mirus, recovered in both southern and southeastern Iran, representing the first record of the species after its original description. As an update to the characteristics of this species, it's all juvenile developmental stages were recovered and described. The criteria to separate L. mirus from two closely related species, L. auratus and L. africanus, are discussed. The third species belongs to L. persicus, a new record in southern Iran. The fourth species, L. orientalis was recovered in high population density in association with date palm trees in Bushehr province. The phylogenetic relationships of the new species and recovered populations of L. mirus and L. persicus were reconstructed using two ribosomal markers and the resulted topologies were discussed.

COMMUNITY SYMPATHY-BASED SLUM SANITATION PLANNING CONCEPT IN BATU BARA DISTRICT, NORTH SUMATERA, INDONESIA

ABSTRACT Slums in the Tanjung Tiram area of Batu Bara Regency are caused by high and uneven population density, limited habitable land and low awareness of environmental conservation among residents. This results in poor environmental sanitation and potentially affects environmental sustainability. The local government is trying to improve this situation through slum upgrading and community empowerment programs. Objectives: This study aims to examine community sympathy for the spatial concept and environmental sanitation improvement programs in Tanjung Tiram neighborhood, as well as the factors that influence it. Methodology and Results: The research method was qualitative with a rationalist approach. The study began with literature analysis and continued with field studies to describe community sympathy in sanitation management, identify patterns of behavior change, and analyze the factors that influence it. Conclusion, Significance, and Implication: The results highlight that the community demonstrated empathy through responsibility and mutual concern for the interests of others, such as involvement in the sanitation improvement process from preparation to monitoring in terms of toilet and bathroom use. Community motivation comes from cadre interventions that provide understanding, increase empathy and responsibility, and strengthen community motivation in sanitation management. Community cooperation and awareness must be increased through community empowerment programs.

Drivers, changes, and impacts of hydrological extremes in India: A review

AbstractThe frequency of hydrological extremes (droughts and floods) has increased in recent years in India. A dense population, intensive agriculture, and rapidly developing physical infrastructure put India under the risk of hydrological extremes. However, a comprehensive overview of the drivers, changes, and impacts associated with hydrological extremes in India has been lacking. We examine the key processes and the role of climate and human interventions on hydrological extremes in India. We discuss the observed and projected changes in hydrological extremes along with their impacts. While the Indian summer monsoon is the primary driver of the hydrological extremes in India, human interventions (irrigation, reservoir storage, and groundwater pumping) play a crucial role in the changes and variability of hydrological extremes. The relative role of climate change and direct human interventions on changing the intensity and impacts of hydrological extremes need to be considered for future adaptation planning under climate change. The observed increase in the frequency and intensity of hydrological extremes will continue in the future with compound and cascading impacts due to the warming climate. We need to strengthen the observational network, improve hydrological modeling, reduce climate uncertainty, and develop robust early warning systems to adapt and mitigate hydrological extremes in India.This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water Extremes Science of Water > Water and Environmental Change

MODELING THE SPREAD OF COVID-19 DISEASE WITH TIME DELAY IN PONTIANAK CITY

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by a coronavirus originating from the city of Wuhan in 2019. This disease affects the respiratory system. The city of Pontianak has the highest population density in West Kalimantan. This density results in a higher spread of Covid-19. In this article, the spread of COVID-19 is formulated into a mathematical model, equilibrium points are sought, stability is analyzed, and a delay time is introduced to reduce the spread of COVID-19. The magnitude of the delay time given during quarantine complies with health protocols, which is between 2 – 14 days. This article aims to analyze the influence of the delay time in modeling the spread of Covid-19. The problem of COVID-19 spread is constructed into an SIQR model, with a sub-population of recovered individuals returning to the susceptible sub-population. The population is divided into four sub-populations: susceptible (S), Infected (I), Quarantined (Q), and Recovered (R). The parameters used include the natural birth rate ( ), the rate of susceptibility to infection ( ), the rate of infection under quarantine ( ), the recovery rate from infection ( ), the recovery rate from infection under quarantine ( ), the death rate from infection ( ), the death rate under quarantine ( ), the delay time from infection to quarantine process ( ), the natural death rate ( ), and the rate of recovered immunity returning to susceptibility ( ). The simulation results show that when the basic reproduction number is less than , the disease-free equilibrium is stable, and when the basic reproduction number is greater than , the endemic equilibrium point is stable. The addition of a time delay ( ) in the SIQR model affects the stability of the endemic equilibrium point but does not affect the stability of the disease-free equilibrium point.

Sociodemographic Heterogeneity in the Associations of Social Isolation With Mortality

There are limited data on whether the vulnerabilities and impacts of social isolation vary across populations. To explore the association between social isolation and mortality due to all causes, cardiovascular diseases (CVD), and malignant neoplasms focusing on heterogeneity by sociodemographic factors. This cohort study used a moderator-wide approach to examine the heterogeneity in the association of social isolation with all-cause, CVD, and malignant neoplasm mortality using baseline data from the Japan Gerontological Evaluation Study in 2010 and 2011. Eligible participants were adults aged 65 years or older without heart disease, stroke, cancer, or impaired activity of daily living across 12 Japanese municipalities. Follow-up continued until December 31, 2017, identifying 6-year all-cause, cardiovascular disease (CVD), and malignant neoplasm mortality. Logistic regression assessed effect modification by age, gender, education, income, population density, marital status, and employment on mortality associations. Data analysis was performed from September 13, 2023, to March 17, 2024. Social isolation, determined by a 3-item scale (scores of 2 or 3 indicating isolation) was the primary exposure variable. Six-year all-cause, CVD, and malignant neoplasms mortality. This study included 37 604 older adults, with a mean (SD) age of 73.5 (5.9) years (21 073 women [56.0%]). A total of 10 094 participants (26.8%) were classified as experiencing social isolation. Social isolation was associated with increased all-cause (odds ratio [OR], 1.20 [95% CI, 1.09-1.32]), CVD (OR, 1.22 [95% CI, 0.98-1.52]), and malignant neoplasm mortality (OR, 1.14 [95% CI, 1.01-1.28]). Stratified analysis showed associations of social isolation with all-cause and malignant neoplasm mortality among people with high income (highest tertile all cause: OR, 1.27 [95% CI, 1.06-1.53]; malignant neoplasm: OR, 1.27 [95% CI, 1.02-1.60]), living in areas with high population density (highest tertile all cause: OR, 1.47 [95% CI, 1.26-1.72]; malignant neoplasm: OR, 1.38 [95% CI, 1.11-1.70]), not married (all cause: OR, 1.33 [95% CI, 1.15-1.53]; malignant neoplasm: OR, 1.25 [95% CI, 1.02-1.52]), and retirees (all cause: OR, 1.27 [95% CI, 1.14-1.43]; malignant neoplasm: OR, 1.27 [95% CI, 1.10-1.48]). Formal testing for effect modification indicated modification by population density and employment for all-cause mortality and by household income and employment for neoplasm mortality. Social isolation was associated with increased risks of all-cause, CVD, and malignant neoplasm mortality, with associations varying across populations. This study fills an important gap in research on social isolation, emphasizing its varied associations across demographic and socioeconomic groups.

The adaptive value of density-dependent habitat specialization and social network centrality

Density dependence is a fundamental ecological process. In particular, animal habitat selection and social behavior often affect fitness in a density-dependent manner. The Ideal Free Distribution (IFD) and niche variation hypothesis (NVH) present distinct predictions associated with Optimal Foraging Theory about how the effect of habitat selection on fitness varies with population density. Using caribou (Rangifer tarandus) in Canada as a model system, we test competing hypotheses about how habitat specialization, social behavior, and annual reproductive success (co)vary across a population density gradient. Within a behavioral reaction norm framework, we estimate repeatability, behavioral plasticity, and covariance among social behavior and habitat selection to investigate the adaptive value of sociality and habitat selection. In support of NVH, but not the IFD, we find that at high density habitat specialists had higher annual reproductive success than generalists, but were also less social than generalists, suggesting the possibility that specialists were less social to avoid competition. Our study supports niche variation as a mechanism for density-dependent habitat specialization.

A unified dataset for pre-processed climate indicators weighted by gridded economic activity

Although high-resolution gridded climate variables are provided by multiple sources, the need for country and region-specific climate data weighted by indicators of economic activity is becoming increasingly common in environmental and economic research. We process available information from different climate data sources to provide spatially aggregated data with global coverage for both countries (GADM0 resolution) and regions (GADM1 resolution) and for a variety of climate indicators (total precipitations, average temperatures, average SPEI). We weigh gridded climate data by population density, night-time light intensity, cropland, and concurrent population count – all proxies of economic activity – before aggregation. Climate variables are measured daily, monthly, and annually, covering (depending on the data source) a time window from 1900 (at the earliest) to 2023. We pipeline all the preprocessing procedures in a unified framework, and we validate our data through a systematic comparison with those employed in leading climate impact studies.